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Gera??o de nuvem de pontos a partir da decomposi??o Gaussiana do sinal LASER com Algoritmos Genéticos

机译:利用遗传算法从激光信号的高斯分解中生成点云

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Recent developments in LIDAR technology lead to the availability of the waveform systems, which capture and digitize the whole return of the emitted LASER pulse. As many objects may cause multiple returns in the same echo, one task is to detect and separate different echoes within the same digitized measurement. In this paper the results of a study aimed at LASER signal waveform decomposition using genetic algorithms are introduced. The proposed method is based on the Gaussian decomposition approach and analyzes each digitized return to compute one or more points. Initially, the number of peaks contained in the waveform is determined by a simple peak detection method, with a local maximum point algorithm. When more than one peak is detected, genetic algorithms are applied to estimate the amplitude, time and standard deviation of each peak within the digitized signal. With this methodology it was possible to increase the number of points by approximately 17 % compared to the point cloud obtained using commercial software. The best results were obtained in areas with high vegetation, and thus the methodology can be applied to the generation of denser points cloud in forest areas.
机译:LIDAR技术的最新发展导致了波形系统的可用性,该波形系统捕获并数字化了发射激光脉冲的整个返回。由于许多物体可能在同一回波中引起多次回波,因此一项任务是检测并分离同一数字化测量中的不同回波。本文介绍了针对使用遗传算法对激光信号波形分解进行研究的结果。所提出的方法基于高斯分解方法,并分析每个数字化收益以计算一个或多个点。最初,通过简单的峰值检测方法和局部最大值算法确定波形中包含的峰值数量。当检测到一个以上的峰时,将应用遗传算法来估计数字信号内每个峰的幅度,时间和标准偏差。与使用商业软件获得的点云相比,使用这种方法可以将点数增加大约17%。在高植被的地区获得了最好的结果,因此该方法可用于在森林地区生成密集的点云。

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